Artificial Intelligence in Organizations – How AI is Changing Management and Supporting Business

The development of artificial intelligence (AI) in recent years has undergone a true revolution. Since OpenAI released ChatGPT in November 2022, the world of technology has changed beyond recognition. AI has ceased to be a curiosity for programmers and has become a real tool used by companies worldwide. Today, artificial intelligence supports business, automates processes, and changes the way organizations are managed.

In this article, you will learn:

• how AI has developed in recent years,

• what language models (LLM) and RAG technology are,

• how AI copilots work,

• what AI agents are and how they support QMS (quality management systems).

Rapid AI development – from ChatGPT to multimodal models

On November 30, 2022, OpenAI released ChatGPT, a tool based on the GPT-3.5 language model. Within just five days, it gained one million users. This marked the beginning of a new era in which artificial intelligence started to be widely used – not only by IT specialists but also by HR departments, customer service, marketing, and quality management.

In March 2023, the GPT-4 model was introduced, and by May 2024 – GPT-4o. The new version offers multimodal capabilities, meaning the model can analyze text, images, sound, and video simultaneously. Thanks to this, AI can understand context even better and respond to user needs more effectively.

Language Models (LLM) – powerful, but limited

LLMs, or Large Language Models, can generate answers, translations, summaries, and even create reports and analyses. However, in the early years of their development, they had a significant limitation — lack of access to an organization’s internal data. They were trained on general internet data, which meant they couldn’t provide responses tailored to a specific business.

Fortunately, a technology has emerged that solved this problem — RAG.

What is RAG? A new era of AI in business

RAG (Retrieval-Augmented Generation) is a breakthrough technology that enables language models to combine their content generation abilities with access to specific information stored in company databases, documents, and systems.

How does RAG work?

• Retrieval – First, the AI searches available sources (e.g., documents, knowledge bases, reports).

• Generation – Based on the retrieved information, it generates an accurate and context-aware response.

  
  

Benefits of RAG for organizations:

• Access to up-to-date data – The model uses current information, not just what it "learned" during training.

• Control over knowledge sources – The organization chooses which data the AI can access.

• No need to train the model – Just provide access to the right documents.

• Responses aligned with company policy and tone – The model adheres to internal guidelines.

Example applications of RAG:

• Automatic responses to customer inquiries

• Summarizing internal documents

• Analyzing quality documentation

Copilot AI – Artificial intelligence with access to tools 

RAG allows AI to use data, but what if dynamic information is needed, such as the current hourly labor rate in a specific department? In such situations, the language model must be able to actively retrieve data from organizational systems. This is where the concept of AI Copilots comes in.

What is a Copilot?

An AI Copilot is a model that, in addition to generating responses, has access to specific tools and functions, such as APIs, databases, or calculators. Depending on the need, it can:

• retrieve data from an ERP or CRM system,

• calculate costs,

• perform SQL queries,

• generate documents and charts.

Examples of using a Copilot in a company:

• QMS (quality management) – analyzing data from production and complaint reports.

• HR – generating responses for employees about vacations, benefits, or training.

• Finance – automatic budget calculations and reporting support.

• Customer service – analyzing inquiries and recommending actions.

AI Agents – a new level of automation

When we combine language models, RAG technology, and Copilot functions, we get something even more powerful – AI agents

Who are AI agents?

AI agents are autonomous, intelligent software units that can:

• understand goals and tasks,

• plan actions,

• make decisions,

• perform tasks using tools.

They are like virtual employees who can support different areas of the organization – without the need for constant supervision.

AI agents in QMS (quality management):

• They monitor compliance with ISO standards.

• They support internal audits.

• They analyze complaints and suggest corrective actions.

• They create automatic reports for management.

• They assist communication between quality, production, and management departments.

The future of AI in business – flexible, intelligent support for every department

Thanks to technologies like RAG, Copilot, and AI agents, organizations gain powerful tools that support daily operations. Moreover, implementing AI no longer requires huge budgets or teams of developers. More and more solutions are available “off the shelf” and can be tailored to the specific needs of a company.

Key benefits of implementing AI in an organization:

• Faster access to knowledge and analyses.

• Time savings for employees.

• Better decision-making.

• Greater consistency in communication and reporting.

• Ability to scale without increasing headcount.

Summary

Artificial intelligence has come a long way – from simple chatbots to AI agents that can support business processes at every level. Today, companies can use modern language models integrated with organizational knowledge and tools, allowing them to operate faster, more efficiently, and more securely.

If your organization is not yet using AI – now is the best time to start. With RAG, Copilots, and AI agents, you can transform your processes, gain a competitive advantage, and successfully implement digital transformation.